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each edge is defined not by interaction of 2 nodes (as in graphs), but 2 sets of nodes (known as hypernodes in hypergraphs)……The use of hypernodes also represents three concepts better than directed or non-directed graphs: protein complexes, protein assemblies and regulation (especially involving complexes/assemblies).
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Signaling hypergraphs. Ritz et al. (2014) TIB

This opinion paper advocates the use of hypergraphs to complement graph-based signaling network and pathway analyses, where each edge is defined not by interaction of 2 nodes (as in graphs), but 2 sets of nodes (known as hypernodes in hypergraphs). They argue that
hypergraphs is a set-based method that acts like a more general version of a graph. The use of hypernodes also represents three concepts better than directed or non-directed graphs: protein complexes, protein assemblies and regulation (especially involving complexes/assemblies). They propose that hypergraphs can be very useful in situations where the effects of individual proteins might be neglected in graphs but will have a noticeable effect when these proteins are included in protein complexes as hypernodes. They use 3 applications as examples: pathway enrichment, pathway reconstruction, and pathway crosstalk.